research article open access estimates of the ......these major shifts can result in the...

RESEARCH ARTICLE Open Access

Estimates of the reproduction number forseasonal, pandemic, and zoonotic influenza: asystematic review of the literatureMatthew Biggerstaff1*, Simon Cauchemez2, Carrie Reed1, Manoj Gambhir3 and Lyn Finelli1

Abstract

Background: The potential impact of an influenza pandemic can be assessed by calculating a set of transmissibilityparameters, the most important being the reproduction number (R), which is defined as the average number ofsecondary cases generated per typical infectious case.

Methods: We conducted a systematic review to summarize published estimates of R for pandemic or seasonalinfluenza and for novel influenza viruses (e.g. H5N1). We retained and summarized papers that estimated R forpandemic or seasonal influenza or for human infections with novel influenza viruses.

Results: The search yielded 567 papers. Ninety-one papers were retained, and an additional twenty paperswere identified from the references of the retained papers. Twenty-four studies reported 51 R values for the1918 pandemic. The median R value for 1918 was 1.80 (interquartile range [IQR]: 1.47–2.27). Six studiesreported seven 1957 pandemic R values. The median R value for 1957 was 1.65 (IQR: 1.53–1.70). Four studiesreported seven 1968 pandemic R values. The median R value for 1968 was 1.80 (IQR: 1.56–1.85). Fifty-sevenstudies reported 78 2009 pandemic R values. The median R value for 2009 was 1.46 (IQR: 1.30–1.70) and wassimilar across the two waves of illness: 1.46 for the first wave and 1.48 for the second wave. Twenty-fourstudies reported 47 seasonal epidemic R values. The median R value for seasonal influenza was 1.28 (IQR:1.19–1.37). Four studies reported six novel influenza R values. Four out of six R values were <1.

Conclusions: These R values represent the difference between epidemics that are controllable and causemoderate illness and those causing a significant number of illnesses and requiring intensive mitigationstrategies to control. Continued monitoring of R during seasonal and novel influenza outbreaks is needed todocument its variation before the next pandemic.

Keywords: Reproductive number, Influenza, Pandemics, Zoonotic influenza

BackgroundAnnual influenza epidemics occur worldwide and causesubstantial morbidity and mortality [1]. In the UnitedStates between 5% and 20% of the population are in-fected with influenza every year [2], resulting in between3,000 and 49,000 influenza-associated deaths [3]. Influ-enza viruses are constantly changing either through thecollection of minor point mutations or through majorantigenic shifts. These major shifts can result in the

introduction of novel influenza viruses into the humanpopulation to which humans have little or no immunity,causing pandemics [1]. Four influenza pandemics haveoccurred since the beginning of the 20th century andhave ranged widely in transmissibility and clinicalseverity [1,4].Recognizing that the characteristics of future pande-

mics will be difficult to predict given the mutability of theinfluenza virus and the range of morbidity and mortalityexperienced in previous pandemics, an approach to theearly assessment of influenza pandemics has been deve-loped relying on standardized measures of transmissibi-lity and clinical severity [5]. An important transmissibility

* Correspondence: [email protected] and Prevention Branch, Influenza Division, National Center forImmunization and Respiratory Diseases, Centers for Disease Control andPrevention, 1600 Clifton Road NE MS A-32, Atlanta 30333, GeorgiaFull list of author information is available at the end of the article

© 2014 Biggerstaff et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of theCreative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use,distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons PublicDomain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in thisarticle, unless otherwise stated.

Biggerstaff et al. BMC Infectious Diseases 2014, 14:480http://www.biomedcentral.com/1471-2334/14/480

parameter identified is the reproduction number (R),which is defined as the average number of secondary casesgenerated per typical infectious case [6,7]. R describes onaverage how many persons a case will infect, and a valueof R greater than 1 indicates that the infection may growor persist in the population while a value of R less than 1indicates that the infection will decline in the population,although exceptions exist [7,8]. Many methods to calculateR have been described that allow for the use of epidemio-logic data from different epidemic time points [7]. Someexamples include estimating R using the growth rate ofthe epidemic, the epidemic curve’s size and shape, thefinal attack rate, or by direct observation of disease trans-mission from one generation to the next [7]. The popula-tion susceptibility to the infection also affects theinterpretation of R. If R is calculated in a population en-tirely susceptible to infection (or where an assumptionabout population susceptibility to infection is made), thenR is known as the basic reproduction number (R0). In con-trast, the effective reproduction number (RE) is calculatedin a population with underlying immunity and accountsfor a population’s reduced susceptibility to infection [9].The value of R characterizes the final number infected

in the absence of an intervention in homogeneouslymixed populations, the herd immunity threshold, and,when coupled with the generation time, defined as theinterval between infections in two consecutive genera-tions, or the serial interval, defined as the interval be-tween the onset of symptoms in two consecutivegenerations), the speed with which the disease spreadsin the population [10-12]. Therefore, the magnitude of Rplays an important role in the selection and aggressive-ness of countermeasures (e.g. social distancing, treatingill individuals, or vaccination) required to slow transmis-sion of the disease [10,13].Because R is used as a measure of transmissibility and

informs the selection of different mitigation strategies, itis important to understand the range and uncertainty ofpublished R values. In this paper, we investigate whetherpublished estimates of R differ between pandemic, sea-sonal, and novel influenza, we compare values of R cal-culated in differing geographic regions and settings, andwe explore the assumptions and limitations of the esti-mation methods of R.

MethodsWe performed a literature search using the PubMeddatabase from 1950 to January 16, 2013. The followingkey terms were searched: “reproduction number and in-fluenza”, “reproductive number and influenza”, “R0 andinfluenza”, “reproduction rate and influenza”, and “re-productive rate and influenza”. We limited our search toarticles in English. We retained articles that estimated Rfor pandemic or seasonal influenza or for human

infections with non-human influenza viruses (e.g. H5N1).For all studies retained, we abstracted the date of pub-lication, the year, the geographic location where the datawere collected, the influenza subtype, the study popu-lation, whether it was a confined setting, the wave of theobservation (if during a pandemic), the estimated valueof R, the method to identify influenza cases, and whe-ther it was a R0 or RE. If multiple R values were provi-ded, we provide the median and range. Since methodsto estimate the reproduction number often require avalue for the generation time or the serial interval, wealso report those values [14]. We classified the methodused to determine influenza-associated cases into twocategories: laboratory confirmed, which required the useof confirmatory testing of respiratory or blood specimens,or unconfirmed, which relied on syndromic case defini-tions to identify cases and required no laboratory con-firmation of illnesses.Median R values and interquartile ranges (IQR) were

reported for each pandemic and for the group of inter-pandemic seasonal epidemics. If a range of values wasgiven for an individual study instead of a point estimate,the middle value of the range was used in the pandemicor epidemic median calculations.

ResultsThe search strategy initially identified 567 papers(Figure 1). Ninety-one papers were retained that esti-mated R for pandemic or seasonal influenza or for humaninfections with non-human influenza viruses (e.g. H5N1).Twenty additional papers were contributed by thereferences of the papers identified through the originalsearch. In all, 111 articles were retained that presented ori-ginal estimates of the reproduction number (summarizedin Tables 1, 2, 3, 4, 5 and 6). Data provided in the tablesare also available as .csv files in Additional files 1, 2, 3, 4, 5and 6.

1918 influenza pandemicThe origins of the 1918 influenza A/H1N1 pandemic areunknown, and illnesses are thought to have occurred inthree waves [1,37]. The first wave began in the NorthernHemisphere in the spring 1918 [1]. A second wave ofmore intense transmission occurred concurrently inNorth America, Europe, and Africa in fall 1918, and athird and final wave occurred in some areas of the worldduring winter 1919 [37,125]. The 1918 pandemic wasthe most deadly pandemic ever recorded, and an esti-mated 675,000 deaths occurred in the United States dur-ing the pandemic period. In contrast to seasonalinfluenza, which disproportionately affects the veryyoung and old, those aged 20–40 years were especiallyaffected [37].

Biggerstaff et al. BMC Infectious Diseases 2014, 14:480 of 20http://www.biomedcentral.com/1471-2334/14/480

Twenty-four studies reported 51 separate 1918 pan-demic values of R (Table 1; Figure 2). The median pointestimate of R in the community setting for all waves ofillness was 1.80 (IQR: 1.47–2.27) (Table 1). A higher me-dian R value (R = 3.82; IQR: 2.68–4.84) was reported inconfined settings, such as ships, military camps, andschools. The median values of R were similar betweenthe first and subsequent waves of illness: the medianvalue of R was 1.81 (IQR: 1.50–2.28) for the 1st wave,1.73 (IQR: 1.39–2.33) for the second wave, and 1.70(IQR: 1.55–1.76) for the third wave (Table 1).The majority of 1918 pandemic values for R were cal-

culated for populations in Europe, which accounted for58% of the R estimates included in this analysis. Themean generation time or serial interval used in the cal-culations to estimate R had a median value of 3.3 days,and the mean ranged from 1.5–6 days. Because the in-fluenza virus was not discovered until 1931[1], all studiesincluded in this review relied on reports of uncon-firmed illness to identify those ill. A majority (65%) usedpneumonia-and-influenza-related hospitalizations anddeaths as the case ascertainment source (Table 1).

1957 influenza pandemicThe 1957 influenza A/H2N2 pandemic began in Febru-ary 1957 in southern China and spread to Singapore andHong Kong in April [1]. The virus was first isolated inthe United States in June 1957 and was associated with a

first wave [1,41]. The peak of the pandemic occurredduring the second wave in the Northern Hemisphere inOctober 1957 and was followed by a third wave in Janu-ary 1958. An estimated 115,000 deaths occurred in theUnited States during the pandemic period [37].Six studies reported seven separate 1957 pandemic

values of R (Table 2; Figure 3). The median point esti-mate of R in the community setting for the second waveof illnesses was 1.65 (IQR: 1.53–1.70). No R values werereported for confined settings or for the 1st or 3rd wavesof illness.A majority (86%) of 1957 pandemic R values were cal-

culated for populations in Europe. The mean generationtime or serial interval used in the calculations to deter-mine R had a median value of 3.5 days, and the meanranged from 2.6–4.1 days. All studies but one includedin this review relied on an unconfirmed illnesses to iden-tify those ill. The other study relied on the final attackrate as determined by serological methods (Table 2).

1968 influenza pandemicThe 1968 influenza A/H3N2 pandemic began in HongKong in July 1968. Large single waves were reported inthe Northern Hemisphere between September 1968 andApril 1969 (with peaks occurring in December and Janu-ary) and in the Southern Hemisphere between June andSeptember 1969. Some countries in the Northern Hemi-sphere, such as the United Kingdom, did not have an

Figure 1 PRISMA flowchart of the article selection for the reproductive number and influenza literature review.


Table 1 Reproduction numbers from the 1918 Influenza A/H1N1 Pandemic

Location Wavea Studypopulation

MeanGT/SIb

ReproductionNumber (R)

95% CIc Basic oreffective

Case definition Reference Yearpublished

Australia 1st Community 2.6 1.80 1.6–2.0 Basic Unconfirmedhospitalizations/deaths

[15] 2008

Brazil 1st Community 4 2.68 Basic Unconfirmed illness [16] 2007

Canada 1st Community 3 1.50 1.5–1.5 Basic Unconfirmed deaths [17] 2011

Canada 1st Community 6 2.1 2.1–2.1 Basic Unconfirmed deaths [17] 2011

Colombia 1st Community 3 1.4–1.5 Effective Unconfirmed deaths [18] 2012

Colombia 1st Community 4 1.5–1.7 Effective Unconfirmed deaths [18] 2012

Denmark 1st Community 2.6 2.2–2.4 Effective Unconfirmed illness [19] 2008

Denmark 1st Community 4 2.8–3.0 Effective Unconfirmed illness [19] 2008

Denmark 1st Community 2.6 2.8–4.0 Effective Unconfirmedhospitalizations

[19] 2008

Denmark 1st Community 4 3.6–5.4 Effective Unconfirmedhospitalizations

[19] 2008

Italy 1st Community 3 1.03 1.00–1.08 Basic Unconfirmedhospitalizations

[20] 2011

Mexico 1st Community 3 1.30 Effective Unconfirmed deaths [21] 2010

Peru 1st Community 3 1.38 1.37–1.40 Effective Unconfirmed deaths [22] 2011

Switzerland 1st Community 3.11 1.49 1.45–1.53 Basic Unconfirmedhospitalizations

[23] 2006

Switzerland 1st Community 3.4 1.50 Basic Unconfirmed deaths [24] 2009

UnitedKingdom

1st Community 2.6 1.7 Basic Unconfirmed deaths [10] 2006

UnitedKingdom

1st Community 4.1 2.10 Effective Unconfirmed illness [25] 2006

UnitedKingdom

1st Community 6 2.00 Basic Unconfirmed illness [26] 2005

UnitedKingdom

1st Community NR 1.16–2.94 Effective Unconfirmed illness [27] 2010

UnitedKingdom

1st Students NR 1.43–5.36 Effective Unconfirmed illness [27] 2010

USA 1st Community 4 1.34–3.21 Effective Unconfirmed illness [28] 2008

Various 1st Community 4 1.2–3.0 Effective Unconfirmed illness [29] 2007

Various 1st Community 4 2.1–7.5 Effective Unconfirmed illness [29] 2007

1st Sailors 4 4.97 Effective Unconfirmed illness [28] 2008

Canada 2nd Community 3.6 2.26 1.95–2.63 Basic Unconfirmed illness [30] 2010

Canada 2nd Community 3.6 1.49 1.42–1.55 Basic Unconfirmed illness [30] 2010

Canada 2nd Community 3 2.40 2.4–2.5 Basic Unconfirmed deaths [17] 2011

Canada 2nd Community 6 4.3 4.2–4.4 Basic Unconfirmed deaths [17] 2011

Denmark 2nd Community 2.6 1.22–1.24 Effective Unconfirmed illness [19] 2008

Denmark 2nd Community 4 1.29–1.33 Effective Unconfirmed illness [19] 2008

Denmark 2nd Community 2.6 1.2–1.3 Effective Unconfirmedhospitalizations

[19] 2008

Denmark 2nd Community 4 1.3–1.4 Effective Unconfirmedhospitalizations

[19] 2008

Germany 2nd Community 1 1.58 0.03–10.3 Basic Unconfirmed deaths [31] 2007




outbreak of H3N2 until the winter of 1969–70. In all, anestimated 110,000 deaths occurred in the United Statesduring the pandemic period [37].Four studies reported seven separate 1968 pandemic

values of R (Table 3; Figure 3). The median point esti-mate of R in the community setting for all waves of ill-ness was 1.80 (IQR: 1.56–1.85) (Table 3). Only twovalues for R in confined settings were reported, and themedian value was 1.39. Two values of R were reportedin a community setting during the first wave and threeduring the second wave. The median value of R duringthe 1st wave was 1.56 and 1.68 during the 2nd wave(Table 3).The 1968 pandemic values for R were calculated

among populations in diverse geographic locations,mainly because of one study that calculated separatevalues for over 25 locations, such as Africa, Asia, andSouth America (the overall estimate for R is included in

Table 3) [43]. The mean generation time or serial in-terval used in the calculations to determine R had a me-dian value of 4 days with little variation. The studies forthe 1968 pandemic included in this review relied on amix of laboratory-confirmed, unconfirmed illnesses, orserologically-confirmed infections to identify those ill(Table 3).

The 2009 influenza pandemicThe 2009 influenza A/H1N1 pandemic began in Mexicoin the late winter or early spring 2009 [44]. The UnitedStates and the United Kingdom experienced a first waveof illnesses in the spring followed by a second wave dur-ing the fall [4]. However, a number of other countries,especially in the Southern Hemisphere, only experienceda single wave of illnesses [100]. In all, an estimated12,000 deaths occurred in the United States during thefirst year of pandemic circulation [126].

Table 1 Reproduction numbers from the 1918 Influenza A/H1N1 Pandemic (Continued)

Italy 2nd Community 3 1.38 1.3–1.5 Basic Unconfirmedhospitalizations

[20] 2011

Mexico 2nd Community 3 1.30 Effective Unconfirmed deaths [21] 2010

NewZealand

2nd Military >1.5 1.3–3.1 Basic Unconfirmedhospitalizations

[32] 2006

Switzerland 2nd Community 2.28 3.75 3.6–3.9 Effective Unconfirmedhospitalizations

[23] 2006

Switzerland 2nd Community 3.4 2.40 Basic Unconfirmed deaths [24] 2009

UnitedKingdom

2nd Community 3 1.39 1.36–1.43 Effective Unconfirmed deaths [33] 2008

UnitedKingdom

2nd Community 6 1.84 1.75–1.92 Effective Unconfirmed deaths [33] 2008

UnitedKingdom

2nd Community 6 1.55 Basic Unconfirmed illness [26] 2005

UnitedKingdom

2nd Community 2.6 1.50 Basic Unconfirmed deaths [10] 2006

USA 2nd Community 2.5 2.14 Basic Unconfirmed deaths [34] 2009

USA 2nd Community NR 2.20 1.55–2.84 Effective Unconfirmed illness [35] 2007

USA 2nd Community 4 2.00 1.7–2.3 Effective Unconfirmed deaths [36] 2004

USA 2nd Community 2.85 1.73 Effective Unconfirmed deaths [14] 2007

UnitedKingdom

3rd Community 3 1.39 1.29–1.49 Effective Unconfirmed deaths [33] 2008

UnitedKingdom

3rd Community 6 1.82 1.61–2.05 Effective Unconfirmed deaths [33] 2008

UnitedKingdom

3rd Community 6 1.70 Basic Unconfirmed illness [26] 2005

Median reproduction number for the 1918 pandemic: 1.80; Interquartile range 1.47–2.27aThe first wave of illnesses began in the Northern Hemisphere in the spring 1918 [1]. A second wave of more intense transmission occurred concurrently in NorthAmerica, Europe, and Africa in the Fall of 1918 while a third and final wave of activity occurred in some areas of the world during the winter of 1919 [37].bThe generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.cConfidence interval.NR = Not reported.This table is also available as a .csv file as Additional file 1.


Fifty-seven studies reported 78 separate 2009 pan-demic values of R (Table 4; Figure 4). The median pointestimate of R in the community setting for all waves ofillness was 1.46 (IQR: 1.30–1.70) while a higher medianR value (R = 1.96; IQR: 1.50–2.23) was reported in con-fined settings, such as military or summer camps,

schools, and night clubs. The value of R was similaracross the two distinct waves of illness: the median valueof R was 1.47 (IQR: 1.31–1.71) for the first wave and1.48 (IQR: 1.30–1.66) for the second wave (Table 4).A majority of 2009 pandemic values for R were calcu-

lated for populations in North America (30%) and Asia

Table 2 Reproduction numbers from the 1957 influenza A/H2N2 pandemic


MeanGT/SIb

Reproductionnumber (R)



Netherlands 2nd Community 3 1.39 Basic Unconfirmed deaths [38] 2010

UnitedKingdom

2nd Community 2.6 1.70 Basic Unconfirmed deaths [10] 2006

UnitedKingdom

2nd Community 3 1.5–1.6 Basic Unconfirmed illness [39] 2008

UnitedKingdom

2nd Community 4 1.7–1.8 Basic Unconfirmed illness [39] 2008

UnitedKingdom

2nd Community 4.1 1.50 Effective Unconfirmed illness [25] 2006

UnitedKingdom

2nd Community NR 1.65 Basic Serology confirmedinfection

[26] 2005

USA 2nd Community 4 1.70 Basic Unconfirmed illness [40] 2004

Median reproduction number for the 1957 pandemic: 1.65; Interquartile range 1.53–1.70aThe 1957 influenza A/H2N2 pandemic began in February 1957 in southern China and spread to Singapore and Hong Kong in April [1]. The virus was first isolatedin the United States in June 1957 and was associated with a mild first wave of illnesses [1,41]. The peak of the pandemic occurred during the second wave in theNorthern Hemisphere in October 1957 and was followed by a third wave in January 1958.bThe generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.cConfidence interval.NR = Not reported.This table is also available as a .csv file as Additional file 2.



MeanGT/SIb




HongKong

1st Community 2.95 1.89 Basic Unconfirmed illness [42] 1986

various 1st Community 4 1.06–2.06 Basic Serology; laboratory confirmedillness; unconfirmed illness

[43] 2010

various 1st Confinedsettings

4 1.08–1.62 Basic Serology; laboratory confirmedillness; unconfirmed illness

[43] 2010

UnitedKingdom

1st Community 4.1 1.80 Effective Unconfirmed illness [25] 2006

UnitedKingdom

2nd Community NR 1.85 Effective Serology confirmed infection [26] 2005

various 2nd Community 4 1.08–2.02 Effective Serology; laboratory confirmedillness; unconfirmed illness

[43] 2010

various 2nd Confinedsettings

4 1.43 1.23–1.63 Effective Serology; laboratory confirmedillness; unconfirmed illness

[43] 2010

Median reproduction number for the 1968 pandemic: 1.80; Interquartile range 1.56–1.85.aThe 1968 influenza A/H3N2 pandemic began in Hong Kong in July 1968. Large single waves of illness were reported in the Northern Hemisphere betweenSeptember 1968 and April 1969 (with peaks occurring in December 1968–January 1969). Large single waves of illnesses were reported in the SouthernHemisphere between June and September 1969. Some countries in the Northern Hemisphere, such as the United Kingdom, did not have an outbreak of H3N2until the winter of 1969–70.bThe generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.cConfidence interval.NR = Not reported.This table is also available as a .csv file as Additional file 3.




MeanGT/SIb




Mexico 0 Community 1.91 1.25 0.76–1.74 Basic Laboratory confirmed illness [44] 2011

Australia 1st Community 2.8 1.50 1.50–2.70 Effective Laboratory confirmed illness [45] 2010



Australia, rural 1st Community 2.9 1.28 1.26–1.30 Effective Laboratory confirmed illness [47] 2011

Australia, urban 1st Community 2.9 1.26 1.22–1.30 Effective Laboratory confirmed illness [47] 2011

Canada 1st Community 1.91 1.30 1.12–1.47 Basic Laboratory confirmed illness [48] 2010




Chile 1st Community 2.5 1.80 1.6–2.0 Effective Unconfirmed emergency room visits [51] 2010

Chile, central 1st Community 3 1.32 1.27–1.37 Effective Unconfirmed hospitalizations [52] 2012

Chile, northern 1st Community 3 1.19 1.13–1.24 Effective Unconfirmed hospitalizations [52] 2012

Chile, southern 1st Community 3 1.58 1.45–1.72 Effective Unconfirmed hospitalizations [52] 2012

China 1st Community 2.6 1.25 1.22–1.28 Effective Laboratory confirmed illness [53] 2012

China 1st Community 4.31 1.53 1.45–1.60 Basic Laboratory confirmed illness [54] 2012

China 1st Community NR 1.68 Basic Laboratory confirmed illness [55] 2011

Hong Kong 1st Community 3 1.70 1.6–1.8 Effective Laboratory confirmed illness [56] 2010

Hong Kong 1st Community 3.2 1.45 1.4–1.5 Effective Laboratory confirmed illness [57] 2010

Israel 1st Community 2.92 1.06 0.97–1.16 Effective Laboratory confirmed illness [58] 2011

Italy 1st Community 2.6 1.30 1.23–1.32 Effective Unconfirmed illness [59] 2012

Japan 1st School 1.9 2.30 2.0–2.6 Effective Laboratory confirmed illness [60] 2009

Japan 1st Community 2.7 1.28 1.23–1.33 Effective Laboratory confirmed illness [60] 2009

Mexico 1st Community 1.91 1.58 1.34–2.04 Basic Unconfirmed illness [61] 2009

Mexico 1st Community 1.96 1.42 Basic Unconfirmed illness [62] 2010

Mexico 1st Community 2.6 1.40 1.2–1.9 Basic Laboratory confirmed illness [61] 2009


Mexico 1st Community 3 1.80 1.78–1.81 Effective Unconfirmed illness [63] 2011

Mexico 1st Community 3 1.43 1.29–1.57 Effective Laboratory confirmed illness [64] 2009

Mexico 1st Community 3.1 2.20 2.1–2.4 Effective Laboratory confirmed illness [65] 2009


Mexico 1st Community 3.6 1.75 1.6–1.9 Basic Seeding from Mexico [66] 2009

Mexico 1st Community 4.1 3.10 2.9–3.5 Effective Laboratory confirmed illness [65] 2009

Mexico City 1st Community 3 1.72 Basic Laboratory confirmed illness [67] 2009

Morocco 1st Community 2.3 1.44 1.32–1.56 Basic Laboratory confirmed illness [68] 2012

Morocco 1st Community 2.7 1.40 1.34–1.48 Basic Laboratory confirmed illness [68] 2012

Netherlands 1st Community 3 0.50 Effective Laboratory confirmed illness [69] 2009

New Zealand 1st Community 2.7 1.25 1.07–1.47 Effective Laboratory confirmed illness [70] 2011

New Zealand 1st Community 2.8 1.96 1.80–2.15 Effective Laboratory confirmed illness [71] 2009

New Zealand 1st Community 2.8 1.55 1.16–1.86 Effective Laboratory confirmed illness;unconfirmed illness

[72] 2010

North America 1st Community 2.7 1.3–2.1 Basic Laboratory confirmed illness [73] 2010

Peru 1st Community 2.8 1.37 1.33–1.41 Effective Laboratory confirmed illness [74] 2009

Peru 1st Community 3 1.30 1.3–1.3 Effective Unconfirmed illness [75] 2011


Table 4 Reproduction numbers from the 2009 influenza A/H1N1 pandemic (Continued)

Peru, Lima 1st Community 3 1.70 1.6–1.7 Effective Unconfirmed illness [75] 2011

Singapore 1st Dance club 1.91 1.9–2.1 Basic Laboratory confirmed illness [76] 2010

Singapore 1st Military NR 1.91 1.50–2.36 Effective Laboratory confirmed andunconfirmed illness

[77] 2010

South Africa 1st Community 2.3 1.43 1.38–1.49 Effective Laboratory confirmed illness [78] 2012



SouthernHemisphere

1st Community 1.9 1.16–1.53 Effective Laboratory confirmed illness [79] 2010

SouthernHemisphere

1st Community 2.60 1.33 1.28–1.45 Basic Laboratory confirmed andunconfirmed illness

[80] 2011

Taiwan 1st Community 1.91 1.14 1.04–1.25 Effective Laboratory confirmed illness [81] 2011

Taiwan 1st Community NR 1.16 0.98–1.34 Effective Serology confirmed infection [82] 2011

Thailand 1st Community 1.9 1.78 1.67–1.89 Basic Laboratory confirmed illness [83] 2009

Thailand 1st Community 2.6 2.07 1.92–2.22 Basic Laboratory confirmed illness [83] 2009

UnitedKingdom

1st School 2.2 1.33 1.11–1.56 Effective Laboratory confirmed illness [84] 2012

UnitedKingdom

1st Community 2.5 1.44 1.27–1.63 Effective Laboratory confirmed illness [85] 2009

USA 1st Community 2.2 1.70 1.4–2.1 Basic Laboratory confirmed illness [86] 2009

USA 1st Community 2.6 2.20 1.4–2.5 Basic Laboratory confirmed illness [86] 2009

USA 1st School 2.7 3.30 3.0–3.6 Effective Unconfirmed illness [87] 2009

USA 1st Community 3.5 1.3–2.0 1.0–2.2 Basic Laboratory confirmed illness [11] 2009

USA 1st Campattendees

7 2.20 1.4–3.3 Effective Unconfirmed illness [88] 2011

Vietnam 1st Community 1.9 1.50 1.5–1.6 Basic Laboratory confirmed illness [89] 2010

Vietnam 1st Community 3.6 2.00 1.9–2.2 Basic Laboratory confirmed illness [89] 2010

worldwide 1st Community 2.67 1–2 Effective Laboratory confirmed illness [90] 2011

China 2nd Community 4 1.66 1.27–2.05 Effective confirmed hospitalizations [91] 2012

China 2nd Community 4.3 1.70 1.4–1.9 Effective Laboratory confirmed illness [92] 2010

France 2nd Military 2.9 1.5–1.6 Effective Unconfirmed illness [93] 2012

Iran 2nd school NR 1.28 1.05–1.54 Basic Unconfirmed illness [94] 2012

Italy 2nd Community 2.5 1.33 Effective Unconfirmed illness [95] 2011

Japan 2nd Community 3 1.48 1.41–1.56 Effective Unconfirmed illness [96] 2012

Mexico 2nd Community 3 1.62 1.61–1.63 Effective Unconfirmed illness [63] 2011

Reunion Island 2nd Community 2.8 1.26 1.08–1.49 Effective Unconfirmed illness [97] 2010

Taiwan 2nd Community 1.91 1.02 1.01–1.02 Effective Laboratory confirmed illness [81] 2011

Taiwan 2nd Community NR 1.87 1.68–2.06 Effective Serology confirmed infection [82] 2011

UnitedKingdom

2nd Community 2.5 1.30 1.2–1.5 Effective Laboratory confirmed illness [98] 2010

Mexico 3rd Community 3 1.24 1.23–1.24 Effective Unconfirmed illness [63] 2011

various Community NR 1.30 1.1–1.4 Effective Serology confirmed infection [99] 2012

Median reproduction number for the 2009 pandemic: 1.46; Interquartile range 1.30–1.70aThe 2009 influenza A/H1N1 pandemic began in Mexico in the late winter or early spring of 2009 [44]. The United States and the United Kingdom experienced afirst wave of illnesses in the Spring of 2009 followed by a second wave during the Fall of 2009 [4]. However, unlike these three countries, a number of countries,especially in the Southern Hemisphere, only experienced a single wave of illnesses [100].bThe generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.cConfidence interval.NR = Not reported.This table is also available as a .csv file as Additional file 4.


Table 5 Reproduction numbers from seasonal influenza epidemics

Year(s) Type/Subtype

Studypopulation

MeanGT/SIa


95% CIb Basic oreffective


1889–1890

H3N8? USA & Europe 2.6 2.10 1.9–2.4 Basic Unconfirmed deaths [101] 2010

1948–1949

H1N1 Canada 4.1 1.30 Effective Unconfirmed illness [25] 2006

1949–1950

H1N1 Canada 4.1 1.50 Effective Unconfirmed illness [25] 2006

1950–1951

H1N1 Canada & UK 4.1 2.00 1.9–2.5 Effective Unconfirmed deaths [25] 2006

1958–1973

H2N2;H3N2; B

UnitedKingdom

4.48 3.9–7.1 Effective Unconfirmed illness [102] 1979

1972–2002

H1N1/H3N2/B

Australia 5.5 1.30 Effective Unconfirmed deaths [103] 2008

1972–2002

H1N1/H3N2/B

France 5.5 1.30 Effective Unconfirmed deaths [103] 2008

1972–2002

H1N1/H3N2/B

USA 5.5 1.30 Effective Unconfirmed deaths [103] 2008

1972–2002

H1N1/H3N2/B

USA; France;Australia

5.5 1.30 1.2–1.4 Effective Unconfirmed deaths [103] 2008

1975–2004

H1N1/H3N2/B

Norway 6 1.06–1.69 Effective Unconfirmed deaths [104] 2010

1976–1981

H1N1/H3N2/B

USA 2.6 1.70 Basic Serology confirmedinfection

[10] 2006

1976–1981

H1N1/H3N2/B

USA 4.1 1.16 Basic Serology confirmedinfection

[105] 2000

1977–1978

H1N1 UnitedKingdom

2.2 4.38 Basic Unconfirmed illness [106] 2005

1977–1978

H1N1 UnitedKingdom

3 21.00 Basic Unconfirmed illness [13] 2004

1977–1978

H1N1 UnitedKingdom

4.70 16.90 Basic Unconfirmed illness [106] 2005

1984–1985

H1N1/H3N2

France 2.49 1.37 Effective Unconfirmed illness [107] 1988

1985–2005

H1N1/H3N2/B

UnitedKingdom

2.2 1.6–2.1 Basic Unconfirmed illness [108] 2010

1985–2005

H1N1/H3N2/B

UnitedKingdom

2.7 1.6–2.5 Basic Unconfirmed illness [109] 2012

1985–2006

H1N1/H3N2/B

France 2.4 1.4–1.7 1.3–1.8 Basic Unconfirmed illness [110] 2008

1996–2006

H1N1/H3N2/B

Brazil 3 1.03 1.02–1.04 Effective Unconfirmed deaths [111] 2010

1998–1999

H3N2 Israel 3 1.14 Effective Unconfirmed illness [112] 2011

1998–1999


1998–1999

H3N2 USA 3 1.18 1.05–1.25 Effective Laboratory confirmedillness

[113] 2009

1998–2009

H1N1/H3N2/B

Israel 2.5 1.17–1.62 Effective Unconfirmed illness [114] 2012

1999–2000


1999–2000



(26%). The mean generation time or serial interval used inthe calculations to determine R had a median value of2.8 days, and the mean ranged from 1.9–7 days (Table 4).A majority of the studies included for the 2009 pandemicrelied on either laboratory-confirmed illnesses (71%) orunconfirmed illnesses (24%) to identify those ill (Table 4).

Seasonal influenzaSeasonal influenza causes sustained epidemics in the non-tropical areas of the Northern Hemisphere and SouthernHemisphere during their respective late fall to early springmonths. Epidemics in the tropical regions occur sporadicallybut can be associated with the rainy season [1]. The

Table 5 Reproduction numbers from seasonal influenza epidemics (Continued)

1999–2006

SeasonalH1N1

Taiwan 2 1.19 0.76–1.86 Basic Confirmed andunconfirmed illness

[115] 2010

1999–2006

H3N2 Taiwan 3 1.41 0.92–2.19 Basic Confirmed andunconfirmed illness

[115] 2010

1999–2006

B Taiwan 3 1.07 0.69–1.69 Basic Confirmed andunconfirmed illness

[115] 2010

2000–2001


2000–2009

H1N1/H3N2/B

Italy 4 1.17–1.36 Effective Unconfirmed illness [116] 2012

2001–2002


2001–2002


2003–2004


2003–2004


2003–2004

H3N2 Switzerland 2.6 1.2–1.3 Effective Unconfirmed illness [117] 2011

2004–2005


2004–2005


2004–2005

unspecified Taiwan 4.1 1.00 Effective Unconfirmed deaths [118] 2010

2004–2005

H3N2 USA 7 1.20 1.1–1.3 Effective Laboratory confirmedillness

[119] 2008

2006–2007


2006–2007


2007–2008


2007–2008


2011/12 H1N1 Mexico 3 1.20 Effective Laboratory confirmedhospitalizations

[120] 2012


[121] 2012


[121] 2012

Median reproduction number for seasonal influenza: 1.28; Interquartile range 1.19–1.37aThe generation time (GT) or serial interval (SI) assumed in the reproduction number estimationbConfidence intervalNR = Not reportedThis table is also available as a .csv file as Additional file 5.


Table 6 Reproduction numbers from novel influenza outbreaks

Year(s) Subtype StudyPopulation

MeanGT/SIa


95% CIb Basic orEffective

Case definition Reference YearPublished

1976 H1N1 New Jersey 1.9 1.20 1.1–1.4 Basic Serologically confirmedillness

[122] 2007

2004–2006

H5N1 Vietnam 7 0.00 0–0.42 Effective Laboratory confirmedillness

[119] 2008

2004–2006

H5N1 Indonesia 7 0.00 0–0 Effective Laboratory confirmedillness

[119] 2008

2005 H5N1 Turkey 9.5 <1 Basic Laboratory confirmedillness

[123] 2007

2005–2009

H5N1 Indonesia 6 0.1–0.25 0–0.4 Effective Laboratory confirmedillness

[124] 2012

2006 H5N1 Indonesia 9.5 1.14 0.61–2.14 Basic Laboratory confirmedillness

[123] 2007

Median reproduction number for novel influenza outbreaks: 0.34; Interquartile range 0.05–0.98aThe generation time (GT) or serial interval (SI) assumed in the reproduction number estimation.NR = Not reported.bConfidence interval.This table is also available as a .csv file as Additional file 6.

Figure 2 Estimates of the reproduction number for the 1918 influenza A/H1N1 pandemic according to location, wave of illness,setting, and the serial interval or generation time assumed in the estimation method. For individual studies, the single estimate or medianof multiple estimates is shown as a circle for basic reproduction numbers or a square for effective reproduction numbers, and the range orconfidence interval is denoted by brackets. Estimates of the reproduction number are color coded based on the generation time or serial intervalused in calculations: red (<3 days), blue (≥3 days), or black (not reported or not used).


mortality burden from influenza varies by season, and from1976–2007, estimates of annual influenza-associated deathsin the United States from respiratory and circulatory causesranged from 3,000 to 49,000 [3].Twenty-four studies reported 47 separate seasonal epi-

demic values of R (Table 5; Figure 5). The median pointestimate of R in the community setting for seasonal in-fluenza was 1.27 (IQR: 1.19–1.37) while a higher medianR value (R = 16.9) was reported in a British boardingschool during the 1977–78 influenza season (Table 5). Rvalues for seasons where H3N2 (R = 1.25; IQR: 1.18–1.27) or H1N1 (R = 1.25; IQR: 1.18–1.35) predominatedwere equivalent (Table 5).A majority of seasonal influenza values for R were cal-

culated for populations in Israel (35%), Europe (25%),and North America (21%). The mean generation time orserial interval used in the calculations to determine Rhad a median value of 3.0 days, and the mean ranged

from 2.0–7.0 days (Table 5). A majority of the studies in-cluded for seasonal influenza relied on unconfirmed ill-nesses or deaths (79%); the reminder relied on eitherlaboratory-confirmed illnesses or hospitalizations orserologically-confirmed infections (Table 5).

Human infections with non-human influenza virusesHuman infections with novel or non-human influenzaviruses (also known as zoonotic influenza viruses) arerare but can result in a pandemic if sustained person-to-person transmission occurs and the population haslittle or no pre-existing population immunity to thevirus. Therefore, instances of infection with non-human influenza viruses are investigated thoroughly toassess the transmissibility of the virus. The largestnumber of novel influenza cases at the time of this re-view was from the ongoing influenza A/H5N1 out-break centered in Southeast Asia and the Middle

Figure 3 Estimates of the reproduction number for the 1957 influenza A/H2N2 and the 1968 influenza A/H3N2 pandemics accordingto location, wave of illness, setting, and the serial interval or generation time assumed in the estimation method. For individual studies,the single estimate or median of multiple estimates is shown as a circle for basic reproduction numbers or a square for effective reproductionnumbers, and the range or confidence interval is denoted by brackets. Estimates of the reproduction number are color coded based on thegeneration time or serial interval used in calculations: red (<3 days), blue (≥3 days), or black (not reported or not used).


East. From January, 1, 2003 to February 15, 2013, 620laboratory-confirmed cases have been reported to theWHO, of which 367 have died [127]. Another largeoutbreak of novel influenza occurred in 1976 in FortDix, New Jersey, which was caused by an influenzaA/H1N1 virus similar to those found circulating inswine [122].Four studies estimated the values of R for the A/H5N1

and A/H1N1 outbreaks (Table 6). Four out of six esti-mates (67%) of R were less than one, and the highestR estimate (R = 1.2) was for the 1976 A/H1N1 out-break in a New Jersey military camp (a confined setting)(Table 6).A majority of novel A virus R values were calculated for

populations in Southeast Asia (67%), indicative of wherethe bulk of A/H5N1 bird-to-human transmission occurs.The mean generation time or serial interval used in thecalculations to determine R had a median value of 7.0 days,

and the mean ranged from 1.9–9.5 days (Table 6). Allstudies relied on either laboratory-confirmed illness orserological-confirmed infection (Table 6).

DiscussionIn this review, the median R values reported for the fourpandemics and seasonal influenza varied between 1.27–1.8 while R values for novel influenza were generallybelow 1. We found the highest median reproductionnumber associated with the 1918 and the 1968 influenzapandemics (both 1.8), followed by the 1957 pandemic(1.65), the 2009 pandemic (1.46), seasonal influenza epi-demics (1.27), and novel influenza outbreaks. A majorityof R values published were for either the 1918 pandemicor the 2009 pandemic; the 1957 and 1968 pandemicshad the fewest published studies. Researchers calculatedvalues for R for a variety of locations and utilized many

Figure 4 Estimates of the reproduction number for the 2009 Influenza A/H1N1 pandemic according to location, wave of illness,setting, and the serial interval or generation time assumed in the estimation method. For individual studies, the single estimate or medianof multiple estimates is shown as a circle for basic reproduction numbers or a square for effective reproduction numbers, and the range orconfidence interval is denoted by brackets. Estimates of the reproduction number are color coded based on the generation time or serial intervalused in calculations: red (<3 days), blue (≥3 days), or black (not reported or not used).


different case definitions, ascertainment methods, andassumptions about the generation time or serial interval.The approximate basic reproductive numbers for some

common infectious diseases range from 12–18 for mea-sles, 12–17 for pertussis, and 4–7 for mumps, polio, ru-bella, and smallpox [12]. These values are much higherthan what has been reported for influenza, and most Rvalues reported in this review ranged from 1.0–2.0.However, the overall clinical attack rate and peak dailyincidence of an outbreak, which measures the potentialburden on healthcare services and school and workplaceabsenteeism, are very sensitive to changes in the value ofR within this range. Past research utilizing a number ofassumptions on the symptomatic ratio, contact patterns,and seeding has estimated that the cumulative clinicalattack rates for a pandemic when R = 1.3 ranged from15%–21% and increased to 34%–42% for R = 2.0 [10,11].Similarly, the peak daily attack rate is 0.5% for R = 1.3

and 2.2% for R = 2.0 [10]. Therefore, with only an abso-lute difference in R of 0.7, the clinical attack rates inthese studies more than doubled and the peak daily inci-dence more than quadrupled.Differences in the value of R within this range also

affect the evaluation of potential mitigation strategies (e.g., school closures, vaccination, household isolation) forinfluenza pandemics. Analysis of strategies to mitigatean influenza pandemic have found that the effectivenessof non-travel-related control policies, such as school clo-sures, household quarantine, and vaccination, would de-crease as the value of R increases from 1.0 to 2.0 [10].The success of various vaccination strategies would alsobe more likely for values of R < 1.7 [10,11]. Therefore,the small variations in pandemic R estimates found inthis analysis can have important implications for theoverall impact and success of mitigation efforts for an in-fluenza pandemic. This finding highlights the importance

Figure 5 Estimates of the reproduction number in the community for seasonal influenza epidemics according to location, wave ofillness, and the serial interval or generation time assumed in the estimation method. For individual studies, the single estimate or medianof multiple estimates is shown as a circle for basic reproduction numbers or a square for effective reproduction numbers, and the range orconfidence interval is denoted by brackets. Estimates of the reproduction number are color coded based on the generation time or serial intervalused in calculations: red (<3 days), blue (≥3 days), or black (not reported or not used).


of making precise estimates of R early in a pandemic.Further research should focus on refining methods thatallow for early, robust estimates of R.The results of this analysis reinforce the idea that R is a

measure that captures the transmissibility of an influenzavirus in the population under study and is not an intrinsicvalue. The inputs for its calculation can include the popu-lation contact rate, the probability of infection per contact,the duration of illness, and the percentage of the popula-tion that is susceptible which is affected by the character-istics of the population under study. Therefore, thevariations in the value for R for the same pandemic or sea-sonal outbreak are expected and may be due to the under-lying social and socio-demographic factors of thepopulation studied, public health interventions, and geo-graphical or climatic factors of the location. These varia-tions include the percentage of the source’s populationunder 18 years old; differences in contact patterns be-tween age groups, which vary by country [128,129]; anddifferences in population susceptibility profiles, which var-ied by age group for the 2009 pandemic [130]. Anotherimportant factor that may contribute to the variation isthe season from which data used to estimate R is col-lected. While the effect of weather on the transmissibilityof influenza has not been fully explored, some studies haveshown that the level of absolute humidity is inversely cor-related with influenza transmissibility [131,132]. There-fore, estimates of R should be interpreted in the context ofthe population under study and the season in which datawas collected and direct comparisons of R between popu-lations should be undertaken with caution.Variations in the estimated values of R may also be

driven by changes in surveillance intensity in the samecountry over time. If a country suddenly improves itssurveillance system in response to a pandemic and isbetter able to identify cases, then the number of casesbeing reported will increase, even though the actualnumber of cases occurring will not have changed. Thisincrease in the reported number of cases may increasethe estimated R as the growth rate of the outbreak willincrease [86]. Conversely, the value of R could be artifi-cially lowered if countries implement changes in surveil-lance practices that result in a lower number ofidentified cases, such as reducing screening recommen-dations, or have their surveillance systems overwhelmed.This effect was seen in the United States during the2009 pandemic, when influenza testing for every casebecame unfeasible and testing recommendations werechanged [4].One of the more important methodological assump-

tions that can have a large impact on the estimated valueof R is the length of the serial interval or generation timeused during the estimation of R. Longer serial intervalshave previously been associated with higher estimates of

R when compared to estimates from the same datasetusing shorter serial intervals [9]. In this analysis, esti-mates of R from the 1918, 1957, and 1968 pandemicsutilized higher serial interval values than were used forthe 2009 pandemic or for seasonal influenza. Addition-ally, higher values of R from the 2009 pandemic oftenwere estimated using a generation time or serial intervalof 3 days or more (Figure 4). Therefore, the estimates ofR included in this analysis should be interpreted in thecontext of the serial intervals or generation times usedin the estimation method. Like R, the values for the gen-eration time or the serial interval can vary by the sourcepopulation. Therefore, researchers estimating the valuesof R should strive to use standard estimates of the serialinterval or generation time for influenza or at least in-clude common values in a sensitivity analysis. This willhelp with the comparability of R values across studiesand may aid in the correct interpretation of R estimates.An additional way in which estimates of R may be biasedup or down lies in the choice of estimation procedure it-self. Chowell et al. showed that estimates of R obtainedusing simple epidemic mathematical models varied con-siderably as the model increased in complexity (e.g. theaddition of a period of infection latency or an age-structured population) [35].Although we found no difference in the value of R for

studies using confirmed cases versus unconfirmed casesin the estimation method, the trade-off between the accur-acy of the less specific but more efficient and cost effectivesyndromic data compared to laboratory-confirmed influ-enza infections is unknown. The incubation periods ofnon-influenza respiratory pathogens that co-circulate withinfluenza (e.g. respiratory syncytial virus or rhinovirus)range from a median of 1.9–5.6 days; estimates of R for in-fluenza could either be overestimated or underestimatedduring periods of co-circulation, depending on the in-tensity and identity of the co-circulating respiratory pa-thogen [87]. Future research should focus on estimationof R using laboratory-confirmed cases and hospitaliza-tions and should provide estimates from syndromic datafor comparison.Most studies included in this analysis focused on 1918

or the 2009 pandemic. Only a small number of estimatesof the reproduction number have been reported for thetwo other pandemics of the 20th century (1957 and1968). As a consequence, there is still insufficient infor-mation to fully clarify the transmission dynamics of the1957 and 1968 pandemics. Because historical data areavailable for these pandemics, future research shouldfocus on estimations of R for the 1957 and 1968 pan-demics to better understand the characteristics of thesepandemics.This study generally found higher reproduction num-

bers for confined settings, such as schools, military


bases, or night clubs, except for estimates from the 1968pandemic. Because confined settings increase the inten-sity of transmission by increasing contact rates amongthose ill and well, the values of R presented for out-breaks in confined settings are likely to be much higherthan values of R estimated for the community andshould be interpreted accordingly. While the estimationof R in confined settings may be useful for the assess-ment of the upper bounds of transmissibility, its value isnot directly comparable to estimates of R made in thecommunity setting.This review found, with one exception, a high degree

of consistency in the estimated values of R for seasonalinfluenza epidemics. The only notable exception was theextremely high R values estimated for an outbreak of in-fluenza A (H1N1) in 1978 at a small British boardingschool with 763 male students aged 10–18 who weremostly full boarders [133]. The results of this analysissuggest that the extreme R values reported for this out-break are not typical of seasonal or pandemic influenzaand instead may be the result of the lack of pre-existingimmunity among the students to the strain of influenzaA (H1N1) that caused the outbreak, the extremely highcontact rates likely among a group of boarded students,or a study artifact related to the small number of stu-dents in the study population [13,106,133]. Additionally,the median R value of seasonal influenza (R = 1.27) iswell below the median values seen during the four pan-demics examined in this report. The consistency of sea-sonal R values is even more remarkable given the widevariety of estimation methods, data sources, and as-sumptions used in the studies included here. However,the majorities of seasonal influenza estimates were froma small number of countries. Estimates of R from coun-tries in Africa, Asia, and South America are also neededto determine if values of R for seasonal influenza epi-demics are affected by geographic and social factors.This systematic review is subject to at least three limi-

tations. First, we combined estimates for the basic andeffective reproductive numbers when presenting the me-dian estimates in this study. Even though these valuesmeasure transmission in populations with differing levelsof underlying population immunity, some papers in-cluded in this review did not clearly differentiate be-tween basic and effective reproductive numbers or statethe required population immunity assumptions whenreporting basic reproductive numbers. Therefore, wechoose to present summary values for the basic and ef-fective reproductive numbers together to simplify the re-sults. The tables include whether the reproductivenumber estimate was reported as basic or effective foreach study. Second, we did not assess included studiesfor the type or quality of their methodology or the riskof study bias. Finally, we only included published

estimates of the reproductive number, which may not berepresentative of unpublished reproductive numbervalues.

ConclusionsIn this review, we explored the ranges and uncertainty ofthe values of R estimated for seasonal, pandemic, andnovel influenza. We found that values of R changed overthe course of a pandemic but the effect of the waves var-ied. The value of R is not constant and may be affectedby mitigation strategies, the season, and the populationunder study. The values of R found in this analysis rep-resent the difference between a pandemic that is con-trollable with less intensive mitigation strategies andwould cause moderate amounts of illness to a pandemicthat would require very intensive mitigation strategiesand would cause greater amounts of illness. Continuedmonitoring of R during outbreaks of human infectionswith non-human influenza viruses and in various set-tings throughout future pandemics will be required tofully understand the effects of mitigation, geography,and season.

Additional files

Additional file 1: Reproduction Numbers from the 1918 InfluenzaA/H1N1 Pandemic.




Additional file 5: Reproduction Numbers from Seasonal InfluenzaEpidemics.

Additional file 6: Reproduction Numbers from Novel InfluenzaOutbreaks.

Competing interestThe authors declare that they have no financial or non-financial competinginterests with the publication of this manuscript.

Authors’ contributionsMB led the data collection, analysis, and the writing of the article. SC led theediting of the article and assisted with data interpretation. CR and MGcontributed significantly to data interpretation and reviewed multiple draftsof the article. LF contributed to the design of the study, data interpretation,and reviewed multiple drafts of the article. All authors read and approvedthe final manuscript.

AcknowledgementsWe are particularly grateful for the assistance in the preparation and editingof the manuscript given by Alejandro Perez and Dr. Claudia Campbell.

DisclaimerThe findings and conclusions in this report are those of the authors and donot necessarily represent the official position of the Centers for DiseaseControl and Prevention.


Author details1Epidemiology and Prevention Branch, Influenza Division, National Center forImmunization and Respiratory Diseases, Centers for Disease Control andPrevention, 1600 Clifton Road NE MS A-32, Atlanta 30333, Georgia.2Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris,France. 3National Center for Immunization and Respiratory Diseases, CDC,Atlanta, Georgia.

Received: 11 April 2014 Accepted: 28 August 2014Published: 4 September 2014

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doi:10.1186/1471-2334-14-480Cite this article as: Biggerstaff et al.: Estimates of the reproductionnumber for seasonal, pandemic, and zoonotic influenza: a systematicreview of the literature. BMC Infectious Diseases 2014 14:480.

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